Prediction error in implicit adaptation during visually- and memory-guided reaching tasks.

Human movements are adjusted by motor adaptation in order to maintain their accuracy. There are two systems in motor adaptation, referred to as explicit or implicit adaptation. It has been suggested that the implicit adaptation is based on the prediction error and has been used in a number of motor adaptation studies. This study aimed to examine the effect of visual memory on prediction error in implicit visuomotor adaptation by comparing visually- and memory-guided reaching tasks. The visually-guided task is thought to be implicit learning based on prediction error, whereas the memory-guided task requires more cognitive processes. We observed the adaptation to visuomotor rotation feedback that is gradually rotated. We found that the adaptation and retention rates were higher in the visually-guided task than in the memory-guided task. Furthermore, the delta-band power obtained by electroencephalography (EEG) in the visually-guided task was increased immediately following the visual feedback, which indicates that the prediction error was larger in the visually-guided task. Our results show that the visuomotor adaptation is enhanced in the visually-guided task because the prediction error, which contributes update of the internal model, was more reliable than in the memory-guided task. Therefore, we suggest that the processing of the prediction error is affected by the task-type, which in turn affects the rate of the visuomotor adaptation.

The effect of eccentricity on visual motion prediction in peripheral vision.

The purpose of the current study was to clarify the effect of eccentricity on visual motion prediction using a time-to-contact (TTC) task. TTC indicates the predictive ability to accurately estimate the time-to-contact of a moving object based on visual motion perception. We also measured motion reaction time (motion RT) as an indicator of the speed of visual motion perception. The TTC task was to press a button when the moving target would arrive at the stationary goal. In the occluded condition, the target dot was occluded 500 ms before the time to contact. The motion RT task was to press a button as soon as the target moved. The visual targets were randomly presented at five different eccentricities (4°, 6°, 8°, 10°, 12°) and moved on a circular trajectory at a constant tangent velocity (8°/s) to keep the eccentricity constant. Our results showed that TTC in the occluded condition showed an earlier response as the eccentricity increased. Furthermore, the motion RT became longer as the eccentricity increased. Therefore, it is most likely that a slower speed perception in peripheral vision delays the perceived speed of motion onset and leads to an earlier response in the TTC task.

The Effect of Target Velocity on the Fast Corrective Response during Reaching Movement.

Online motor control is often required to correct errors in rapid adjustments during reaching movements. It has been established that the initial arm trajectory during reaching is corrected by a target displacement. Since this corrective response occurs without perception of target perturbation, this is regarded as an automatic response. However, an object rarely "jumps" in daily life, rather it often "moves" as a chronological change of the position that causes visual motion. Therefore, the purpose of this study was to investigate whether the implicit visuomotor response is induced by target motion stimuli and to clarify the effects of target motion velocity on initial arm trajectory. Participants were asked to move a cursor from a start circle to a visual target. The target moved either leftward or rightward when the cursor passed 20 mm from the start circle. Four target velocities (10, 20, 30, 40 deg/s) were randomly presented. Our results showed that the initial velocity (first 50 ms) of the fast corrective response increased with the target velocity. Therefore, it is indicated that the fast corrective response is induced by the target motion stimulus with a short latency and its amplitude is dependent on the target velocity.

The influence of the motor command accuracy on the prediction error and the automatic corrective response.

The online control system allows for automatic corrective response to unexpected perturbation. This corrective response may involve a prediction error between the sensory prediction by the motor command and the actual feedback signal. Therefore, we attempted to investigate the effect of motor command accuracy on the automatic corrective response. Participants were asked to move a cursor displayed on a monitor and required to reach the center of a Gaussian blob target as accurately as possible for small and large Gaussian blob conditions. The accuracy of the motor command was manipulated by the size of the Gaussian blob. In half of the trials, a perturbation occurred in which the cursor position jumped 10 mm to either the left or right from the actual position, which induced an automatic corrective response. This corrective response was detected by the acceleration signal on the lateral axis. In addition, the prediction error was estimated by the amplitude of the N1 event-related potential (ERP) of the EEG signal. We found that the automatic response and N1 ERP were significantly larger in the small Gaussian blob conditions than in the large one. This result indicates that the automatic corrective response is affected by the certainty of the motor command manipulated by the Gaussian blob. Furthermore, the linear mixed-effect model (LME) indicated that the response is associated with the N1 ERP. Therefore, we suggest that the motor command accuracy affects the prediction error, which in turn modulates the automatic corrective response.

Changes in visual speed perception induced by anticipatory smooth eye movements.

Expectations about forthcoming visual motion shaped by observers' experiences are known to induce anticipatory smooth eye movements (ASEMs) and changes in visual perception. Previous studies have demonstrated discrete effects of expectations on the control of ASEM and perception. However, the tasks designed in those studies were not able to segregate the effects of expectations and execution of ASEM itself on perception. In the present study, we attempted to directly examine the effect of ASEM itself on visual speed perception with a two-alternative forced-choice (2AFC) task, in which observers were asked to track a pair of sequentially presented visual motion stimuli with their eyes and to judge whether the second stimulus (test stimulus) was faster or slower than the first (reference stimulus). Our results showed that observers' visual speed perception, quantified by a psychometric function, shifted according to ASEM velocity. This was the case even though there was no difference in the steady-state eye velocity. Further analyses revealed that the observers' perceptual decisions could be explained by a difference in the magnitude of retinal slip velocity in the initial phase of ocular tracking when the reference and test stimuli were presented, rather than in the steady-state phase. Our results provide psychophysical evidence of the importance of initial ocular tracking in visual speed perception and the strong impact of ASEM.NEW & NOTEWORTHY We provide psychophysical evidence that the execution of anticipatory smooth eye movement (ASEM) leads to underestimation of visual speed perception, that is, observers perceive the object motion velocity as slower than when ASEM is not induced, even though the performance of subsequent ocular tracking is comparable. Moreover, our results showed that such perceptual decisions regarding object motion velocity were derived from the ASEM-induced decrease in retinal slip velocity during the initial phase of ocular tracking.

The relationship between the implicit visuomotor control and the motor planning accuracy.

It has been well established that an implicit motor response can be elicited by a target perturbation or a visual background motion during a reaching movement. Computational studies have suggested that the mechanism of this response is based on the error signal between the efference copy and the actual sensory feedback. If the implicit motor response is based on the efference copy, the motor command accuracy would affect the amount of the modulation of the motor response. Therefore, the purpose of the current study was to investigate the relationship between the implicit motor response and the motor planning accuracy. We used a memory-guided reaching task and a manual following response (MFR) which is induced by visual grating motion. Participants performed reaching movements toward a memorized-target location with a beep cue which was presented 0 or 3 s after the target disappeared (0-s delay and 3-s delay conditions). Leftward or rightward visual grating motion was applied 400 ms after the cue. In addition, an event-related potential (ERP) was recorded during the reaching task, which reflects the motor command accuracy. Our results showed that the N170 ERP amplitude in the parietal electrodes and the MFR amplitude were significantly larger for the 3-s delay condition than the 0-s delay condition. These results suggest that the motor planning accuracy affects the amount of the implicit visuomotor response. Furthermore, there was a significant within-subjects correlation between the MFR and the N170 amplitude, which could corroborate the relationship between the implicit motor response and the motor planning accuracy.

Effects of smooth pursuit and second-order stimuli on visual motion prediction.

The purpose of this study was to determine whether smooth pursuit eye movements affect visual motion prediction using a time-to-contact task where observers anticipate the exact instant that a partially occluded target would coincide with a stationary object. Moreover, we attempted to clarify the influence of second-order motion on visual motion prediction during smooth pursuit. One target object moved to another stationary object (6 deg apart) at constant velocity of 3, 4, and 5 deg/s, and then the two objects disappeared 500 ms after the onset of target motion. The observers estimated the moment the moving object would overlap the stationary object and pressed a button. For the pursuit condition, both a Gaussian window and a random dots texture moved in the same direction at the same speed for the first-order motion, whereas a Gaussian window moved over a static background composed of random dots texture for the second-order motion. The results showed that the constant error of the time-to-contact shifted to a later response for the pursuit condition compared to the fixation condition, regardless of the object velocity. In addition, during smooth pursuit, the constant error for the second-order motion shifted to an earlier response compared to the first-order motion when the object velocity was 3 deg/s, whereas no significant difference was found at 4 and 5 deg/s. Therefore, our results suggest that visual motion prediction using a time-to-contact task is affected by both eye movements and motion configuration such as second-order motion.